AI product Open source
CDAF is an open sidecar format and toolkit for video that stores a timestamped plain-text description beside the corresponding video file. Its Python library and CLI can generate, parse, validate, read, and report the status of `.cdaf` files, while an agent skill teaches video agents to check for a matching sidecar before processing footage.
Each sidecar contains a minimal versioned header with the video filename, SHA-256 hash, byte size, duration, generator, and creation time, followed by sections such as summary, timestamped segments, transcript, on-screen text, and tags. Conforming tools verify the video's freshness and refuse to use a stale sidecar after the video changes; the format is model-agnostic even though the included generator uses the Gemini Files API, with optional local-model support.
The repository includes a normative specification, reproducible sidecar-versus-direct-video benchmarks, an agent skill installable with `npx cdaf-skill`, and CLI commands for generation, validation, reading, and status checks. The core validation functions require only the Python standard library; generation requires Python 3.10 or later and a user-supplied Gemini API key. The project is licensed under MIT.
1 use taken from transcripts — each links to the moment in the video.
Caches a hash-verified plain-text description beside a video so agents can reuse prior analysis instead of reprocessing footage. It rejects stale sidecars and reduces token usage for video questions.
1 in the library.